The present invention generally relates to cybernetic engineering principles applied to the neurophysiological processes of the brain and in particular to a process for neurometric calibration and verification of brain cell-firing frequency patterns representing mental experience. More specifically, this invention discloses a method for attenuating brain activity measurements by comparing evoked responses from stimuli of different form representing the same progression of brain activity.
The process of the present invention is analogous to developing a historical record of a traffic accident by interviewing several witnesses who saw the accident from different perspectives. Thereby a more accurate picture of the events can be obtained through a synthesis of the varying viewpoints.
This invention is based in the antilocalizationist viewpoint of the mechanics of brain functioning. Brain activity is generally measured by EEG procedures. The value of EEG measurements is dependent upon analysis, and analysis is generally made by referencing static templates, i.e. patterns known to represent certain brain conditions. The present invention is a device and method for developing distinct measurable parameters for simultaneous trial of events, or a "dynamic template." Boardgames are used in the art as brain activity stimulators for brain activity measurements.
More recent evidence against the localization of brain function include the recording from a widespread extent of cortex, evoked potentials (Doty, 1958) or responses of single neurons (Burns, Heron, & Grafstein, 1960) to visual stimuli; the ability of visual discrimination after extensive ablations of cortical and collicular regions of the visual system (Urbaitis & Hinsey, 1966; Winans & Meikle, 1966); and among others, the ability for auditory frequency discrimination by cats after bilateral ablation of all cortical auditory areas resulting in complete retrograde degeneration of the medial geniculate body (Goldberg & Neff, 1964).
The initial phases of neuroscientific study concerned itself with investigations of sensory, motor, and reflex functions. More recently, increasing attention has been given to neural activity concerned with behavior. From these more recent investigations, a hypothesis of a centralized integrative system to represent the gross organization responsible for conscious activity has been developed. Consideration of the intrinsic properties of reticular arrangements of neurons with short axons has led to two important conclusions: (1) in reticular systems, the dynamic properties of neurons working en masse predominate over the consequences of activity of single cells; and (2) due to the shortness of most recticular axons, interactions of graduated somatodendritic potentials are more predominant in the control of activity in such systems than axonal spikes.
Information appears to be represented in the brain by the temporal pattern of nonrandomness, or organization, in the firing of ensembles of many neurons rather than by the activity of individual cells. At any moment, a particular anatomic distribution of such nonrandom activity patterns exists in the brain. From each of the various regions of the brain experiencing nonrandom activity, neural outflow propagates to other regions exerting influence which causes further nonrandom activity. The resulting interaction between patterns of organized neural discharge arising, interacting, and subsiding throughout the brain represents the instantaneous fluctuation of information in the system. The organized nature of the activity defines the activity as informational, the anatomic locus of the ensemble defines the modality of the information, and the details of the temporal pattern describe the content of the information.
The different informationally significant facets of momemtary experience is called the representational system for that experience. Similar electrical patterns have been observed in many different brain regions when a familiar event occurs, which reflects the functioning of the distributed anatomic network of the organized neuronal patterns. A representational system is any structure of which the features symbolize or correspond in some sense to some other structure (Mackey, 1969). Consciousness, itself a representational system, is a consequence of the occurence of a set of temporal sequences of nonrandom activity in a set of interacting anatomic structures. The modality of the facets of conscious experience, or form, depends upon the anatomic location of the neuronal ensembles in which the statistical processes emerge. The shape of the separate facets of conscious experience, or content, depends upon the temporal pattern of the nonrandom activity in each of these brain regions.
The prior art has not clearly determined whether or not the informational patterns which constitute the content of consciousness arise in some central integrative system receiving input from all other anatomic regions sustaining informational patterns or arise as a result of the interactions between the various regions. However, the prior art postulates that the content of consciousness is defined by the statistical features of activity in an anatomically diffuse network of neurons, although the precise physical nature of those consequences or the cooperative process which are responsible for consciousness are not understood.
Most recent work within the prior art has further developed certain basic ideas: (1) information in the nervous system is represented by the statistical behavior of neuronal ensembles rather than by the firing of any individual cell; (2) the constituent activities of the ensemble are postsynaptic potentials and axonal spikes, unitary events of transient electrical process, a shift in ionic concentrations and charge densities, which possess gestalt properties not contained in the individual parts; (3) mental experience arises from the cooperative behavior of neuronal ensembles; and (4) the physical properties of the neuronal ensemble processes which generate subjective experience as the result of cooperative behavior of neurons may relate to the ways in which energy is organized by neuronal masses, and may reflect general properties of matter (Thatcher & John, 1977).
The prior art has established that the representation of information within the brain, whether concrete information about the present or abstractions about such information, is organized and statistical in nature. Predictions from such statistical formulations are also supported by experiment. However, the prior art has not determined the processes of change from the organized activity of representational systems, a state of zero entropy, to the universal tendency toward chaos, or positive entropy, asserted by the laws of thermodynamics, and likewise the change processes from predetermined activity of the representational systems of information.
When a sensory stimulus is presented to a human subject, a transient oscillation of voltage occurs in the EEG recorded from electrodes over responsive brain regions, which often is obscured by other ongoing activity. This oscillation, or evoked response, represents the response of the brain to the sensory stimulus and occurs at a latency determined by the central transmission time of the sensory system that was stimulated. By use of an averaging technique, often implemented by a special-purpose average response computer, the details of the waveshape of the voltage oscillations that are time-locked to the delivery of the sensory stimulus can be ascertained from the average evoked response (AER). The visual, somatosensory, and auditory systems all involve a set of specialized peripheral receptors capable of transducing specific environmental energies into nerve impulses which are conducted in what are called "primary sensory" pathways to "relay stations" located in the thalamus. The waveshape of the AER reflects the anatomy of the responding systems, the characteristics of the stimulus, and certain dynamic factors. Averaging evoked responses improve the signal-to-noise ratio, or accuracy of definition of the evoked response, by an amount proportional to the square root of the number of samples obtained.
Since the advent of the average response computer, numerous investigators have discussed the characteristics of the AER in various types of neuropathology, and have drawn inferences about brain function based upon deviations of certain components of the waveshape from some expected normal contour. Such AER methods have won little acceptance in routine clinical practice, perhaps because of the AER waveshape dependence on visual recognition of patterns by the practitioner, a similar shortcoming of qualitative evaluation of the EEG. In order to achieve more precise, objective criteria for EEG diagnosis requires that impressionistic evaluation of the EEG be replaced by numbers and that subjective descriptions be replaced by mathematical characterizations.
The prior art has described a digital electrophysiological data acquisition and analysis system which permits the rapid, automatic acquisition of precise data about a spectrum of functionally significant electrophysiological measures and their reduction to numerical taxanomic classification of such data have also been surveyed. These endeavors have established the theoretical practicality of quantitative and objective evaluation of the combination of neurometric and numerical taxonomic methods. Background research has generally been directed toward use in diagnosis, treatment, and prognosis of diseases and brain dysfunction and the practical utility of these methods has been demonstrated through studies of normal and those suffering from neurological diseases; normal and learning disabled children. Methods for neurometric analysis of the EEG mostly have concerned themselves with objective determination of the frequency distribution, or spectral analysis. The differences in individual perception of a common stimuli necessitates means for calibration and verification of the brain cell-firing frequency pattern measurements.
Most electroencephalographers consider bilateral symmetry of waveform and amplitude an important feature of the EEG, sensitive to neuropathology. Symmetry measures place lower importance on the absolute frequency composition of the EEG signal, and rely more on the use of the EEG from one hemisphere as the "control" relative to the other. Symmetry values are usually comparable and correspond well to the symmetry of the overall EEG activity. Spontaneous EEG reflects ongoing electrical transactions between and within various anatomic regions of the brain related to its intrinsic organization. Evoked response provides insight into the reactivity of various functional systems of the brain to afferent input and tells something about how the system processes different kinds of information. Symmetry measures circumvent the issue of "normal morphology" of brain activity and the interindividual variability in spectral analysis.
Two methods for quantitative evaluation of AER symmetry are (1) cross-correlation between AERs derived simultaneously from bilaterally symmetric derivations and (2) significance of differences between bilateral pairs of AERs. The prior art also includes a symmetry analyzer which measures waveform symmetry based upon utilization of polarity coincidence correlation methods which consist of making a large number of comparisons of the polarity (positivity or negativity) of two simultaneous electrical signals, and measures amplitude symmetry by rectifying and integrating each input signal and computing the ratio of the integrated absolute amplitudes.
Pattern recognition methods include (1) template methods, (2) cluster analysis, (3) discriminant analysis, and (4) multi-dimensional scaling. Template methods employ data analysis procedures involving assumptions about the features of some particular event being sought or the general nature of the structure of the solution to some problem. This method can be viewed as a process of scanning a long train of samples of electrical waveshapes to identify recurrences of the template. Cross-correlation between the template and the train of samples of electrical waveshapes to identify recurrances of the template and using the shifting theorem and the cross-spectral theorem of Fourier analysis are techniques used to rectify measurements of this method. Another method is the adaptive filter method, an extension of the cross-spectral technique where the template is iteratively redefined. All template methods suffer from the constrain of someone specifying the basic characteristics of the process or event describing the template.
Cluster analysis is an analytic method that describes the details characterizing the structure of a body of data. Cluster analysis ascertains, given a set of feature vectors, how many groups are contained within that structure and which elements most probably belong to each group. This method offers the advantage over the template method in that it permits the structure of a body of data to be analyzed in the absence of prior assumptions about the nature of the structure. Nonetheless, some guidance must be provided.
Discriminant analysis can be conceptualized as a mapping of each feature vector into a multivariate space. This is a technique for finding an optimal vector, which minimizes the spread within distributions and maximizes the separation between the centroids or the two sets of points projected upon that vector, thus providing the best possible discrimination between the two bodies of data. Discriminant analysis ascertains, given a set of features characterizing two or several groups of data, which features best discriminate between the two groups and what are the clusters of feature vectors corresponding to the discrimination.
Multi-dimensional scaling is a graphic approach to cluster analysis. It is a method of mapping distances between data points. The original distances are in the (high-dimensional) space of the feature vector, and the distance function is the similarity measure; the final space is a two-(or three-) dimensional space of points with the property that the distances between these points are equal to the original distances. The distance function used in the final space is not necessarily the same as the similarity measure.
In order to make electrophysiological measurements more readily available and more precise, and to extend their utility into new areas of application, the following conditions must be met:
(1) optimal instrumentation must be devised to gather data in a standardized fashion and maximize the efficiency and accuracy of data processing; PA0 (2) a set of challenges must be devised that reflect important aspects of brain function in particular electrophysiological measurements. There is no reason to expect that any stimulus delivered to the central nervous system will provide useful insights into the manner or adequacy with which some particular function is performed by the brain, unless the context of the situation in which the stimulus is imbedded, as well as the stimulus itself, is devised to exercise that particular capability; and PA0 (3) the essential features of each of these measures must be quantified, so that they can be represented numerically and manipulated statistically and mathematically.
A quantitative electrophysiological test battery (NB) has been developed in the prior art. Basic neurometric indices computed for each derivation under each condition defining an EEG measure in the NB include distribution of energy in different frequency bands, age-dependent quotient, energy ratios, energy symmetry, and waveform symmetry. The plausibility of each challenge comprising the NB has not been documented and is based upon findings of previous experiences.
The digital electrophysiological data acquisition and analysis system, and the quantitative electrophysiological test battery developed in the prior art are useless until normative data are acquired, and until systematic correlations are established between the indices of brain function which they provide and functional measures obtained by the conventional techniques of neurology and psychology. Techniques must also be devised to segregate the meaningful numbers (signal) from the meaningless numbers (noise). As well, a method of encompassing the vast body of data produced for an individual by a discrete set of descriptors must be devised. These descriptors must achieve a great deal of data compression for the present system of data acquisition, yielding profiles of deviation from expected or probable values for various functions which permit classes of individuals with similar etiologies to be identified.